Previously, an analytical method was developed to extract the photovoltaic (PV) cell parameters, such as the shunt resistance, R-sh, series resistance, R-s, diode ideality factor, n, and reverse saturation current density,J(0), through the use of the single current density-voltage (J-V) characteristics under high illumination conditions. Accurate knowledge of the PV cell parameters under different illumination conditions is of vital importance to PV design and performance. Although several attempts have been made to examine the dependency of the PV cell parameters on the illumination intensity P-in, there are no reports on the dependence of the PV cell parameters on P-in, under high illumination conditions. In this regards, dependency of the analytically-predicted PV cell parameters on P-in of Si solar cells with various structures has been investigated. The analytically-predicted values of R-sh and R-s decreased with increasing P-in. The rate of change in R-sh, however, was higher than that of R-s. The decrease in R-sh may be due to light induced degradation of PV cells. The decrease in R-s values might be due to an increase in the conductivity of the active region. On the other hand, n and J(0) increased with increasing P-in. This increase in n and J(0) might have a savior effect, reducing the curve factor CF and hence the performance of the PV cell. The rate change in all PV cell parameters was higher at lower P-in values than at the higher P-in values. The theoretically computed values of the open circuit voltage V-oc, curve factor CF and efficiency eta using this method showed good agreement with the experimentally measured values at various P-in. The performance of the PV systems is dependent on the product of the J(sc), V-oc and CF. Therefore, it is important to determine the optimal value of P-in to achieve the maximum output power (minimum losses due to R-sh, R-s, n and J(0)) from a PV system. By doing so, the cost per peak watt of solar energy can be minimized by enhancing the performance of PV systems. (C) 2014 Elsevier Ltd. All rights reserved.